The Diffusion of Innovations: Everett Rogers
Can a rural sociologist who studied animal husbandry in the 1950s have anything to say about the way high-tech products are accepted into the marketplace? Turns out he can. Everett Rogers’ diffusion of innovations theory offers a time-tested framework to parse out some of the factors that may have contributed to an innovation's success or failure. Rogers was instrumental in establishing this systematic study in the ways innovations are introduced to and adopted by potential users.
He provided a framework to compare a large number of innovations using a common vocabulary and set of metrics. Rogers defined diffusion as “the process by which an innovation is communicated through certain channels over time among the members of a social system.” His work was wildly influential well beyond agricultural circles and many of the words he used have made it into common market speak. Innovators, early adopters, the majority, and laggards were terms he used to define the various kinds of potential users of a given innovation and are routinely used to define market segments in all industries.
Rogers began his research by studying the mechanisms by which American farmers successfully adopted the agricultural innovations developed at land-grant universities. In a series of diffusion studies across multiple areas, Rogers found that innovations that have these characteristics-- high relative advantage, trialability, observability, and compatibility, and low complexity--- are likely to succeed over innovations that possess lower levels of those attributes:
Relative advantage is the degree to which an innovation appears to be better than any other alternatives the potential adopter might have, measured in terms of economics, convenience, satisfaction, and social prestige. It is the abstraction of Emerson’s “better mousetrap,” and it has been identified as the most important predictor of an innovation’s adoption rate. Innovations do not typically exist in a vacuum and must compete with other innovations looking to serve the same purpose.
Trialability is the degree in which the innovation can be experienced firsthand on a limited basis. For example, pills for weight control are certainly more triable than having one's stomach surgically tied, and are tried with far more frequency, in spite of their limited effectiveness.
Observability is the degree in which the innovation or its results can be seen by others likely to adopt it. If potential adopters are unaware of the innovation or do not see it being used by their peers, they are less likely to adopt it themselves. If a tree falls in a forest, does it make a sound?
Compatibility is the degree to which the innovation is seen as consistent with existing values, previous experiences, and needs of the user. Innovations exist among other innovations and rest on the experiences potential adopters have had with other innovations and their personal values and beliefs. Some innovations may be seen as a part of a larger group of innovations, known as a technology cluster, and may be judged by potential adopters within the context of the group, rather than individually.
Complexity is the degree in which the innovation is seen as difficult to understand or use. People are less likely to adopt hard to use or complex products.
Rogers and his colleagues conducted a series of diffusion studies in multiple areas that have suggested strong relationships between these factors and successful diffusion. Innovations that have high relative advantage, compatibility, trialability, observability, and low complexity are likely to succeed over innovations that possess higher levels of those attributes.
I was personally able to verify that Everett Rogers's five diffusion factors were as evident in educational technology, as they have been in the multiple industries Rogers and his colleagues studied over the past half-century. In 2006, I conducted a study to examine the factors contributing to the successful diffusion of technological innovations in the K-12 classroom. A series of 37 potential diffusion factors were identified, and 43 educational technology innovations were examined to see if they exhibited those characteristics. The innovations were also given a rating as to how successful they were in the marketplace. Neural network and multiple regression analysis suggested that the same five factors that Rogers identified in his diffusion of innovations research were also the most predictive of an educational innovation's chances of success in the market.
Rogers's diffusion work illustrates a number of basic factors that go beyond simple product marketing techniques, and are required to facilitate true change in education. Innovators would be wise to understand and position their products with these factors in mind. His classic book, Diffusion of Innovations provides more details and is a good guide to making things that people will want to use in the modern era.
About Bill Ferster
Bill Ferster is a research professor at the University of Virginia and a technology consultant for organizations using web-applications for ed-tech, data visualization, and digital media. He is the author of Sage on the Screen (2016, Johns Hopkins), Teaching Machines (2014, Johns Hopkins), and Interactive Visualization (2012, MIT Press), and has founded a number of high-technology startups in past lives. For more information, see www.stagetools.com/consult.